Event info

Date: 12:00~13:00, JST Tuesday, 2 June 2026

Zoom: Online via Zoom

Speaker: Prof. Takaharu YAGUCHI (Kyushu University)

Title: Learning Hamiltonian Systems Using Neural Networks

Abstract:
Recently, methods for learning Hamiltonian equations, which are the equations of motion in Hamiltonian mechanics, from observational data using neural networks have attracted attention. In this talk, I will introduce these methods, with a focus on those that we have developed. Specifically, I will discuss machine learning methods for identifying the hidden symplectic structure, thereby maintaining the laws of physics.

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This seminar series is a valuable opportunity for graduate students to get acquainted with the work of more experienced researchers in various mathematical fields. Undergraduate students are also welcome to join, as the talks are intended for non-experts, too. Regardless of your area of research, you can attend the seminar to expand your knowledge and get in touch with the latest developments in mathematics for industry.
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